A comprehensive sequence for undergraduate engineering students on the perception layer of robotics. It covers sensor noise modeling, Bayesian filters, Kalman filters (KF and EKF), and the fundamentals of SLAM, focusing on how robots interpret noisy real-world data to build a reliable world model.

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